Gas turbines and their blades in particular might be damaged in the course of the aviation turbojet engine operation process. The degradation process of the blade microstructure is most evident from the change in the colour of its surface. This is assessed using the optoelectronic method. The article presents the concept of non-destructive methods, which are used to assess the degree of degradation of the alloy of a gas turbine blade. The proposed optoelectronic method is the basic method for the preliminary determination of color changes in the surface. Appropriate videoscopes or video-analyzers, capable of recording a test object in various electromagnetic wave ranges (infrared radiation, visible range), are used for this purpose. These preliminary results of the diagnosis make it possible to infer further studies of the blade. For accurate investigation of the state of the alloy microstructure, a non-destructive thermographic method (xenon flash pulsed thermography) was used. The results of studies of the degradation of the microstructure with the use of non-destructive methods were verified through the use of metallographic investigations. Appropriate metallographic specimens were created in order to recognize phase γ′ degradation (i.e., the phase strengthening the blade alloy). The results of the presented research allowed for an in-depth assessment of the degree of microstructure degradation of operated blades.

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Biometrics is currently an area that is both very interesting as well as rapidly growing. Among various types of biometrics the human gait recognition seems to be one of the most intriguing. However, one of the greatest problems within this field of biometrics is the change in gait caused by footwear. A change of shoes results in a significant lowering of accuracy in recognition of people. The following work presents a method which uses data gathered by two sensors: force plates and Microsoft Kinect v2 to reduce this problem. Microsoft Kinect is utilized to measure the body height of a person which allows the reduction of the set of recognized people only to those whose height is similar to that which has been measured. The entire process is preceded by identifying the type of footwear which the person is wearing. The research was conducted on data obtained from 99 people (more than 3400 strides) and the proposed method allowed us to reach a Correct Classification Rate (CCR) greater than 88% which, in comparison to earlier methods reaching CCR’s of <80%, is a significant improvement. The work presents advantages as well as limitations of the proposed method.

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